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» Evolving recurrent models using linear GP
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EH
2004
IEEE
107views Hardware» more  EH 2004»
13 years 9 months ago
Evolving Digital Circuits using Multi Expression Programming
Multi Expression Programming (MEP) is a Genetic Programming (GP) variant that uses linear chromosomes for solution encoding. A unique MEP feature is its ability of encoding multipl...
Mihai Oltean, Crina Grosan
ESANN
1998
13 years 6 months ago
Recurrent SOM with local linear models in time series prediction
Recurrent Self-Organizing Map (RSOM) is studied in three di erent time series prediction cases. RSOM is used to cluster the series into local data sets, for which corresponding lo...
Timo Koskela, Markus Varsta, Jukka Heikkonen, Kimm...
AEI
1999
110views more  AEI 1999»
13 years 4 months ago
Self-tuning fuzzy controller design using genetic optimisation and neural network modelling
This article describes a new adaptive fuzzy logic control scheme. The proposed scheme is based on the structure of the self-tuning regulator and employs neural network and genetic...
Duc Truong Pham, Dervis Karaboga
ICPR
2008
IEEE
14 years 6 months ago
Evolving boundary detectors for natural images via Genetic Programming
Boundary detection constitutes a crucial step in many computer vision tasks. We present a novel learning approach to automatically construct a boundary detector for natural images...
Ilan Kadar, Moshe Sipper, Ohad Ben-Shahar
BIOSYSTEMS
2007
115views more  BIOSYSTEMS 2007»
13 years 5 months ago
Evolving fuzzy rules to model gene expression
This paper develops an algorithm that extracts explanatory rules from microarray data, which we treat as time series, using genetic programming (GP) and fuzzy logic. Reverse polis...
Ricardo Linden, Amit Bhaya